In the adaptation phase, it is possible to fine tune the NN further through a reinforcement learning (RL) algorithm.
The training setup varies based on the specific choice of the RL algorithm.
A comprehensive review of reinforcement learning is clearly beyond the scope of this work.
Interested readers may refer to the standard text on this topic [1]}.
Lastly, we remark that this phase may be skipped if the NN trained in the imitation phase is sufficiently effective for the target control application or if the RL algorithm does not bring any improvement to the trained NN.
